Multi-Omics analysis identifies a lncRNA-related prognostic signature to predict bladder cancer recurrence.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34738881", "kind": "science-record", "revision": 4, "content_hash": "sha256:f44c1b51837641fb5dd90fb1939be226eb2d90e6f691b270eab02d1b44720e5a", "created_at": "2026-11-01T17:36:25Z", "updated_at": "2026-11-01T22:05:05Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Multi-Omics analysis identifies a lncRNA-related prognostic signature to predict bladder cancer recurrence.", "doi": "10.1080/21655979.2021.2000122", "pmid": "34738881", "authors": ["Zhipeng Xu", "Hui Chen", "Jin Sun", "Weipu Mao", "Shuqiu Chen", "Ming Chen"], "journal": "Bioengineered", "year": 2021, "abstract": "Bladder cancer (BLCA) is one of the most common cancers worldwide with high recurrence rate. Hence, we intended to establish a recurrence-related long non-coding RNA (lncRNA) model of BLCA as a potential biomarker based on multi-omics analysis. Multi-omics data including copy number variation (CNV) data, mutation annotation files, RNA expression profiles and clinical data of The Cancer Genome Atlas (TCGA) BLCA cohort (303 cases) and GSE31684 (93 cases) were downloaded from public database. With multi-omics analysis, twenty lncRNAs were identified as the candidates related with BLCA recurrence, CNVs and mutations in training set. Ten-lncRNA signature were established using least absolute shrinkage and selection operation (LASSO) and Cox regression. Then, various survival analysis was used to assess the power of lncRNA model in predicting BLCA recurrence. The results showed that the recurrence-free survival time of high-risk group was significantly shorter than that of low-risk group in training and testing sets, and the predictive value of ten-lncRNA signature was robust and independent of other clinical variables. Gene Set Enrichment Analysis (GSEA) showed this signature were associated with immune disorders, indicating this signature may be involved in tumor immunology. After compared with the other reported lncRNA signatures, ten-lncRNA signature was validated as a superior prognostic model in predicting the recurrence of BLCA. The effectiveness of the model was also evaluated in bladder cancer samples via qRT-PCR. Thus, the novel ten-lncRNA signature, constructed based on multi-omics data, had robust prognostic power in predicting the recurrence of BLCA and potential clinical implications as biomarkers.", "claims": [{"id": "claim-method", "statement": "Ten-lncRNA signature were established using least absolute shrinkage and selection operation (LASSO) and Cox regression.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34738881", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Ten-lncRNA signature were established using least absolute shrinkage and selection operation (LASSO) and Cox regression."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Original data were uploaded to a recognized data repository (URL: https://zenodo.org/record/5153530#.YZtEZU5ByUk; DOI: 10.5281/zenodo.5153530)", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34738881", "locator": "sections[31] \"Data availability statement\" paragraph 2", "quote": "Original data were uploaded to a recognized data repository (URL: https://zenodo.org/record/5153530#.YZtEZU5ByUk; DOI: 10.5281/zenodo.5153530)"}], "state": "complete"}, {"id": "claim-target-result", "statement": "Thus, the novel ten-lncRNA signature, constructed based on multi-omics data, had robust prognostic power in predicting the recurrence of BLCA and potential clinical implications as biomarkers.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34738881", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Thus, the novel ten-lncRNA signature, constructed based on multi-omics data, had robust prognostic power in predicting the recurrence of BLCA and potential clinical implications as biomarkers."}, {"asset": "source:pmid:34738881", "locator": "sections[18] \"Validating prognostic power of the relapse-associated lncRNA signature\" paragraph 2", "quote": "AUC for ten-lncRNA signature was 0.73 at the RFS in the fifth year (Figure 3(b))."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Thus, the novel ten-lncRNA signature, constructed based on multi-omics data, had robust prognostic power in predicting the recurrence of BLCA and potential clinical implications as biomarkers.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:34738881"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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